83a4a7b805
The GPU batch sweep processes multi-stage configs round-by-round: at round s every still-alive config with a stage s runs its discharge in one batch, carrying the slug's global position/velocity forward to the next round. Configs with fewer stages drop out of later rounds. Analytic constant-velocity sensor trigger per stage. Validated vs CPU run_coilgun for multi-stage configs (<=3% exit velocity). Default max_stages 4 -> 10. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
48 lines
2.1 KiB
Python
48 lines
2.1 KiB
Python
import json
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from gausse.components.database import ComponentDatabase
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from gausse.gpu.batch_sweep import run_gpu_sweep
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from gausse.optim.search_space import SearchBounds, decode, genome_from_dict
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from gausse.sim.coilgun import run_coilgun
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from gausse.storage.database import count_runs, fetch_runs, open_connection
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DB = ComponentDatabase.load()
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def test_gpu_sweep_records_all_runs(tmp_path):
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db_path = tmp_path / "gpu.sqlite3"
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summary = run_gpu_sweep(db_path, n_runs=300, seed=3, prefer_gpu=False, batch_size=300)
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assert summary["n_runs"] == 300
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conn = open_connection(db_path)
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assert count_runs(conn) == 300
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rows = fetch_runs(conn)
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# многоступенчатые конфиги допустимы (до max_stages)
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stage_counts = set()
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for r in rows:
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g = genome_from_dict(json.loads(r.genome_json))
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stage_counts.add(len(g.stages))
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assert r.search_mode.startswith("gpu-sweep")
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assert max(stage_counts) >= 2, "должны встречаться многоступенчатые конфиги"
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def test_gpu_sweep_matches_cpu_within_tolerance(tmp_path):
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"""Честная сверка: GPU-батч (в т.ч. многоступ.) даёт те же exit_v, что CPU run_coilgun."""
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db_path = tmp_path / "gpu.sqlite3"
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run_gpu_sweep(db_path, n_runs=2000, seed=5, prefer_gpu=False, batch_size=2000)
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conn = open_connection(db_path)
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bounds = SearchBounds()
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feasible = fetch_runs(conn, feasible=True, order_by_efficiency_desc=True, limit=12)
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assert len(feasible) >= 3
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checked = 0
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for r in feasible:
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g = genome_from_dict(json.loads(r.genome_json))
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config, _, _ = decode(g, DB, bounds)
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cpu = run_coilgun(config)
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if not cpu.feasible:
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continue
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# фикс.шаг батча + аналитический триггер vs адаптивный solve_ivp: ~3%
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assert abs(r.exit_velocity_mps - cpu.exit_v_mps) <= 0.03 * abs(cpu.exit_v_mps) + 0.2, \
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f"GPU {r.exit_velocity_mps:.2f} vs CPU {cpu.exit_v_mps:.2f} ({len(g.stages)} ступ.)"
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checked += 1
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assert checked >= 3
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